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On the Nature of Verbal Non-Local Doubling in Patagonian Spanish

Bibliographic Data

ID5900181
AuthorsJosé Silva Garcés (0000-0001-6875-4309, National University of Comahue, corresponding author), G Espinosa (0000-0002-0370-9520, National University of Comahue)
Year2023
Volume8
Issue4
Pages255
Publication date2023-10-26
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueLanguages (JOURNAL)
Journal identifiersISSN: 2226-471X • E-ISSN: 2226-471X
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/languages8040255
OpenAlexW4387957472
LanguageEN
References cited34

The main objective in this study is to describe and offer an account of verbal non-local doubling in Patagonian Spanish (PatSp), an understudied non-standard variety of Spanish in Argentina. We focus on data in which there are duplicated verbs surrounding an XP that bears the nuclear accent of the phrase (XPNA). First, our analysis describes the prosodic, semantic, and morphosyntactic behaviour of the data gathered. Second, we present the problems and challenges that doubling phenomena in PatSp pose for approaches that have tried to explain similar data in other Spanish varieties and other languages, such as the copy theory or prosodic cloning. Third, this work explores a biclausal analysis of verbal non-local doubling in PatSp in which each duplicate originates in a different clause, CP1 and CP2. In this approach, duplicated verbs (V1 and V2, according to their linear distribution) are not derivationally related. We also argue that the XPNA moves to the left periphery of CP2. This movement would account for the three typical traits of verbal duplication in PatSp: the mandatory adjacency between the nuclear accent and V2, the non-locality between verbal duplicates, and the semantic value of mirativity

Focus (optics · Linguistics · Locality · Natural language processing · Phrase · Physics · Stress (linguistics · Computer Science · Phonetics and Phonology Research · Psychology · Spanish Linguistics and Language Studies · Syntax, Semantics, Linguistic Variation · Artificial Intelligence

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